Spectrum spatial structure characteristic analysis of remote sensing alteration information and interference factors

Based on the statistical characteristics of remote sensing data, the spatial geometric structure characteristics of spectral data and distribution of background, interference and alteration information in characteristic space were researched through the analysis of two-dimensional and three-dimensional scatter diagrams. The results indicate that the hyper-space of remote sensing multi-data aggregation belongs to low-dimensional geometric structure, i.e. hyperplane form, and anomalous point groups including alteration information usually dissociate out of hyperplane. Scatter diagrams of remote sensing data band are mainly presented as two distribution forms of single-ellipse and dual-ellipse. Clarifying the relations of three objects of background, disturbance and alteration information in remote sensing images provides an important technical thought and guidance for accurately detecting and extracting remote sensing alteration information.

Pegmatite remote sensing extraction and metallogenic prediction in Azubai area,Xinjiang

Remote sensing technique plays an important role in geological prospecting in Altay because of the remote location and steep terrain with mountains. Pegmatite has important implications for metallogenic prospecting as most of rare metals occurs in it. Pegmatite information from optical and radar images was extracted, and the spatial distribution and scale of pegmatite were generalized in Azubai, Altay. Three mining targets, that is, Halon-Azubai, Kuermutu-Tuyibaguo and Zhuolute-Akuoyige, were delineated based on the analysis of pegmatite information, structure interpretation and other geological data.

Remote Sensing Technology for Identification of Alteration Information of Gold Deposits in the Eastern Tianshan Area, Xinjiang

Based on specific well-exposed rocks useful for high-quality remote sensing interpretation in the gold-prospecting area in the eastern Tianshan, this paper gives a detailed description of a remote sensing model for metallogenic prediction. The model reveals that multi-spectral remote sensing data are integrated with high-resolution remote sensing data, and enhanced extraction and visual description of weak remote sensing information are used for prospecting. This model has tested in the given gold deposit, and used successfully in Au-Cu prospecting in the Kalatage area.

Integrating Aster Images Processing and Fieldwork for Identification of Hydrothermal Alteration Zones at the Oumjrane-Boukerzia District, Moroccan Anti-Atlas

Mapping from remote sensing has become more effective in the field of geology, mainly in lithological discrimination and identification of hydrothermal alteration zones. The use of this technique consists in obtaining information about the rock mass and the main ones existing in the inaccessible areas. Satellite data from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) sensor represent a favorable potential for detecting the spectral signatures of mineral zones and identifying their nature. These data are more reliable in places where the climate is arid with less abundant vegetation, as at the Oumjrane-Boukerzia mining district. This region which is part of the Eastern Anti-Atlas, is composed of several mineralized veins which still require detailed studies and exploration by the technique of remote sensing. In this work we applied several processing techniques on ASTER imagery such as Colored Composition, Principal Component Analysis and Ratio Bands. The use of the reports of the specialized Bands makes it possible to identify some hydrothermal alteration minerals within the mining district of Oumjrane Boukerzia. These minerals are represented mainly by iron oxides and hydroxides (Hematite, jarosite, limonite and goethite), carbonate minerals (dolomite, calcite), clay minerals (Illite, kaolinite and chlorite) and quartz minerals. This work allows us to produce a map of hydrothermal alteration zones which can be used as a valuable reference in the strategy of mining exploration for the base metals (Cu, Pb, Zn and Ba), in the mining district of Oumjrane-Boukerzia and in the entire Eastern Anti-Atlas.

Some essential questions in remote sensing science and technology

In this paper,I propose a personal view on the general contents of remote sensing science and technology,which includes sensor research and manufacturing,remotely sensed data acquisition,data processing,information extraction and remote sensing applications.Serving as the basis for all these components is radiative transfer process modeling and inversion.Also of importance is the effective visualization of remotely sensed data and their efficient distribution to end users.In all these areas,there are critical research questions.In particular,I consider 4 fundamental areas for improved application of remote sensing.These include the scale and angular issues in remote sensing,removal of topographic effects on the radiance and geometry of remotely sensed imagery and the related question of multisource and multitemporal data registration,integrating knowledge and remotely sensed data into effective information extraction,and four dimensional data assimilation techniques.Strategies of information extraction can be broadly divided into manual visual analysis and computer-based analysis.The computer based information analysis include radiative transfer model inversion,image classification,regression analysis,three dimensional information extraction,shape analysis and change detection.Successful information extraction is the key to the success of remote sensing.There are many important issues that need to be solved including how to make better use of the spatial and temporal data present in remotely sensed data in information extraction.How to effectively combine the strength of both computer analysis and human interpretation? Finally,4D data assimilation is the new direction that allows for the integration of instantaneous observation with process-based climate,hydrological and ecological models.Further work along this direction will enhance the contribution of remote sensing in global change studies.In return,the quality of remotely sensed parameters can be improved.

Research on Extraction Method of Surface Information Based on Multi-Feature Combination Such as Fractal Texture

Because of the developed economy and lush vegetation in southern China, the following obstacles or difficulties exist in remote sensing land surface classification: 1) Diverse surface composition types;2) Undulating terrains;3) Small fragmented land;4) Indistinguishable shadows of surface objects. It is our top priority to clarify how to use the concept of big data (Data mining technology) and various new technologies and methods to make complex surface remote sensing information extraction technology develop in the direction of automation, refinement and intelligence. In order to achieve the above research objectives, the paper takes the Gaofen-2 satellite data produced in China as the data source, and takes the complex surface remote sensing information extraction technology as the research object, and intelligently analyzes the remote sensing information of complex surface on the basis of completing the data collection and preprocessing. The specific extraction methods are as follows: 1) extraction research on fractal texture features of Brownian motion;2) extraction research on color features;3) extraction research on vegetation index;4) research on vectors and corresponding classification. In this paper, fractal texture features, color features, vegetation features and spectral features of remote sensing images are combined to form a combination feature vector, which improves the dimension of features, and the feature vector improves the difference of remote sensing features, and it is more conducive to the classification of remote sensing features, and thus it improves the classification accuracy of remote sensing images. It is suitable for remote sensing information extraction of complex surface in southern China. This method can be extended to complex surface area in the future.

Deep learning in extracting tropical cyclone intensity and wind radius information from satellite infrared images—A review

热带气旋(TC)严重危害人类生命和财产安全,TC的实时监测一直是研究热点,随着空间和传感器技术的发展,卫星遥感已成为监测TC的主要手段.此外,深度学习具有卓越的数据挖掘能力,在地球科学中的表现优于基于物理或统计的算法,越来越多的深度学习算法被开发和应用于TC信息的提取,本文系统地回顾了深度学习在TC信息提取中的应用,并给出了深度学习模型在TC强度和风圈半径提取中的应用.此外,本文还展望了深度学习在TC信息提取中的应用前景.

Remote Sensing Estimation of Crop Lead Pollution Stress Degree Using Wavelet Analysis

Accurate estimation of soil lead pollution degree is one of the key steps in controlling soil lead pollution; vegetable hyperspectral features research provided a new approach to discovering and monitoring soil heavy metal pollution.Spectral reflectance implies information of pollution impacts on vegetation;estimation of lead pollution degree based on the spectral reflectance is equivalent to extraction of weak information.This study puts forward a new feature extraction method based

一种基于Landsat 8 OLI影像的水体信息提取方法研究

提出一种基于Landsat 8 OLI影像提取水体信息的斜率比值法(SR),比对不同方法、不同类型水体和不同季节影像的数据,结果表明:SR法相比归一化差异水体指数法(NDWI)和改进的归一化差异水体指数法(MNDWI),水体信息提取精度更高,且对阈值精确度的要求低,阈值一般设定为2.0;SR法适用于清澈水体、浑浊水体、浅水河滩等水体,对河流干流和较大支流的提取精度达到99%,细小支流、沟渠的提取精度为66%,面积较小的水体提取精度为65%;在冬季太阳高度角较低时,SR也能较好地去除阴影。

MSCANet: multiscale context information aggregation network for Tibetan Plateau lake extraction from remote sensing images

Qinghai-Tibet Plateau lakes are important carriers of water resources in the‘Asian’s Water Tower’,and it is of great significance to grasp the spatial distribution of plateau lakes for the climate,ecological environment,and regional water cycle.However,the differences in spatial-spectral characteristics of various types of plateau lakes,and the complex background information of plateau both influence the extraction effect of lakes.Therefore,it is a great challenge to completely and effectively extract plateau lakes.In this study,we proposed a multiscale contextual information aggregation network,termed MSCANet,to automatically extract Plateau lake regions.It consists of three main components:a multiscale lake feature encoder,a feature decoder,and a Multicore Pyramid Pooling Module(MPPM).The multiscale lake feature encoder suppressed noise interference to capture multiscale spatial-spectral information from heterogeneous scenes.The MPPM module aggregated the contextual information of various lakes globally.We applied the MSCANet to the lake extraction of the Qinghai-Tibet Plateau based on Google data;additionally,comparative experiments showed that the MSCANet proposed had obvious improvement in lake detection accuracy and morphological integrity.Finally,we transferred the pre-trained optimal model to the Landsat-8 and Sentinel-2A dataset to verify the generalization of the MSCANet.

植被覆盖区老旧矿山边部遥感蚀变信息提取技术探讨

植被覆盖区基岩裸露少,围岩蚀变信息微弱.为在老旧矿山边部开展找矿工作,通过不同方法实验,最后采用植被抑制+岩土体光谱测试组合技术完成蚀变信息提取.该方法首先运用强迫不变植被抑制技术降低植被干扰,其次采集已有矿山蚀变围岩及蚀变带岩土体光谱信息并建立研究区光谱样本库,最后采用CART决策树分类技术完成蚀变信息提取.实验证明,基于植被抑制技术的CART决策树分类蚀变信息提取方法在植被覆盖区老旧矿山边部遥感蚀变信息提取效果较好.

遥感技术新进展赋能水利行业应用

随着遥感技术的不断发展和水利信息化进程的加快,水利遥感有了飞速的发展,与水利现代化发展同步。目前,遥感技术在水利行业的应用范围非常广,在为水利高质量发展提供有力支撑和强力驱动的数字孪生水利建设中发挥了重要的作用。近十多年来,快速发展的遥感技术为提升水利遥感应用能力提供了强有力的支撑,具体表现在数据源的丰富化和多源化、数据获取的速度和效率显著提升、定量估算与反演精度大大提高、专题信息可获得性不断增加、数据处理和信息提取的智能化水平取得长足进步。介绍了遥感技术发展赋能水利遥感应用领域的现状和前景展望,为遥感技术赋能水利新质生产力提供参考。

一种基于IGA的融合点云和影像的建筑物提取方法

针对精细化实景三维建筑物建模,提出一种基于改进遗传算法(IGA)的建筑物LiDAR点云与正射影像融合提取方法:计算并提取基于点云和影像的特征,实现点云特征空间的扩张;再改进遗传算法选择点云特征,构建并优化特征空间;最后使用SVM分类器实现建筑物点云的精准提取。在ISPRS公开数据集Vaihingen测试数据的试验表明本文方法具有较高的建筑物提取精度;在实际生产数据的实验表明建筑物提取精度较高且稳定,证明了本文方法的先进性和普适性。

Fast Remote-Sensing Image Registration Using Priori Information and Robust Feature Extraction

In this paper, we propose a fast registration scheme for remote-sensing images for use as a fundamental technique in large-scale online remote-sensing data processing tasks. First, we introduce priori-information images,and use machine learning techniques to identify robust remote-sensing image features from state-of-the-art ScaleInvariant Feature Transform（SIFT） features. Next, we apply a hierarchical coarse-to-fine feature matching and image registration scheme on the basis of additional priori information, including a robust feature location map and platform imaging parameters. Numerical simulation results show that the proposed scheme increases position repetitiveness by 34%, and can speed up the overall image registration procedure by a factor of 7：47 while maintaining the accuracy of the image registration performance.

新疆地区西昆仑和田玉遥感信息提取与找矿远景区圈定

新疆地区和田玉主要产在西昆仑至阿尔金一带,这些地区属于高海拔和严寒地区,难以直接开展地质调查工作。当前遥感技术已在热液型矿床的找矿工作中取得重要进展。和田玉矿床属于热液型矿床,地表会留下明显的矿物蚀变信息,通过遥感信息技术寻找和田玉矿床在理论上是可行的。本次研究在西昆仑康西瓦地区,使用哨兵二号、ASTER等多光谱数据和高分5号高光谱数据提取与和田玉矿化有关的蚀变信息,构建了一个以蚀变信息为主的遥感找矿找矿模型,圈定了多处和田玉遥感找矿远景区,并对找矿远景区进行了野外验证。在选取的多个和田玉遥感找矿远景区内,发现了和田玉矿的典型蚀变类型,即蛇纹石化与透闪石化,以及多处出露地表的大理岩和多处正在开采的玉石矿。野外验证结果表明,本次研究采用的和田玉遥感勘查技术是有效的。

高光谱遥感植被图谱信息提取研究进展

高光谱遥感在植被健康检测、植被群落分类以及精准农业等领域得到了广泛的运用,同时,高光谱遥感还能够利用精细的光谱信息来识别物质成分,使植被分类等工作更加精细和准确。高光谱遥感数据的图谱信息具备信息容量大和图谱一体化特点,能够通过连续窄波段获取地表地物信息,并记录植被等地物的光谱信息,同时也记录地物的图形信息。然而,由于数据量庞大且存在冗余,所以高光谱遥感在植被图谱信息提取方面仍面临巨大挑战,本文研究了国内外学者在高光谱植被图谱研究中的重要贡献,分析了高光谱的图谱特征、植被图谱信息提取方法并展开讨论,高光谱技术不仅能提供丰富的植被图谱信息,在其他领域研究中也具有巨大应用潜力。

基于Landsat TM的个旧锡矿成矿信息提取与找矿预测

在对云南个旧锡矿矿区成矿地质环境、地质特征和成矿规律研究的基础上,以Landsat TM多光谱影像数据为基础信息源,利用遥感找矿技术对个旧锡矿地质构造信息和蚀变异常信息进行提取。在此基础上,综合利用已有的地质、物探和化探成果,结合野外实地调查后圈定了3类共9个找矿远景区。

基于Landsat TM的热带精细地物信息提取的模型与方法——以海南岛为例

应用遥感技术进行精细地物信息提取是研究生态系统结构、过程和功能的重要手段之一。由于热带地区生态系统复杂,为精细地物信息提取带来很大的不确定性,极易产生"同物异谱"、"同谱异物"的现象。研究以地处热带地区的海南岛精细地物遥感信息提取为例,在综合分析典型地物光谱特征、空间分布、斑块形状等基础上,构建和优化了水陆指数WLI(Water andLand differing Index)、乔灌草指数GSI(Grass and Shrub differing Index)、旱地-沙地指数SSI(Field and Sand differing Index),并结合新型通用植被指数VIUPD(Vegetation Index of the Universal Pattern Decomposition Method)及DEM(Digital Elevation Model)等多源数据,提出基于决策树的面向对象遥感信息提取方法。该方法首先确定要提取的对象,明确对象类别与对象隶属关系,然后逐层逐项的提取天然林、橡胶林、浆纸林等地物信息。结果表明,综合提取的精度达88%,相比传统的监督分类方法精度(66%)提高22个百分点,精度明显提高。

基于决策树的Landsat TM/ETM+图像中太湖蓝藻水华信息提取

以9期Landsat TM/ETM＋影像为数据源,基于K-T变换和归一化植被指数（NDW）,建立了湖泊蓝藻水华信息提取的决策树模型.基于大气顶面反射率图像,选用2005年10月17日太湖图像进行了对比验证,表明决策树模型比单波段阈值法、多波段阈值法（RVI、DVI、NDW）能够更有效地提取蓝藻水华信息,区分陆生植被、水生植物和水华,省去了水体掩膜的过程.使用太湖2002年10月25日和2011年7月22日图像、巢湖2005年8月12日的图像,验证决策树模型方法和工作流程的有效性.使用多期TM图像确定了阈值的取值范围,其中,亮度、绿度、NDVI的下限值依次为0.191、-0.007、-0.054,湿度下限范围为0.07～0.15;亮度阈值上限范围为0.3～0.7、绿度为0.2～0.5、湿度为0.1～0.3,这些结果可作为湖泊蓝藻水华遥感监测的参考.

基于Landsat-TM影像的鄱阳湖典型湿地动态变化研究

利用分层分类法,通过对鄱阳湖典型湿地（蚌湖与赣江中支口三角洲）长序列秋季Landsat-TM影像进行解译分析,探讨了1991年-2008年间鄱阳湖典型湿地动态变化特征。结果表明分层分类方法能够有效地应用于Landsat-TM遥感影像的解译;从1991年到2008年蚌湖和赣江中支口三角洲湿地的植被面积分别增加18.56km2和6.01km2,其中赣江主支三角洲洲滩植被分布呈向湖体扩展态势。植被分布受水情影响比较大,蚌湖湿地的苔草面积与同时期水面积呈负相关性,而赣江主支三角洲湿地植被类型结构变化受水位影响也比较明显,苔草面积变化与秋季湖口水位表现为负相关,芦苇分布面积变化则与湖口水位变化趋势较为一致。